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SageMaker Clarify

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Amazon SageMaker Clarify

2025-08-29T07:18:48+00:00

Bookmarks Key Capabilities Core Components Configuration Components Bias Metrics Overview SHAP Explainability Validate Your Knowledge Amazon SageMaker Clarify Cheat Sheet Amazon SageMaker Clarify is a SageMaker AI feature for detecting bias and explaining model predictions. Supports both pre-training and post-training bias analysis. Provides feature attribution to explain how input features influence predictions. Can monitor deployed models for bias drift and feature attribution drift over time. Key Capabilities Bias Detection Pre-training bias: Analyzes datasets before model training. Post-training bias: Evaluates model predictions for fairness across facets. Supports binary, multiclass, and regression tasks. Interpreting [...]

Amazon SageMaker Clarify2025-08-29T07:18:48+00:00

Amazon AI Fairness and Explainability with Amazon SageMaker Clarify

2023-12-02T01:24:03+00:00

Introduction In the rapidly evolving domain of machine learning, ensuring fairness and explainability in model predictions has become crucial. With Amazon SageMaker Clarify, these critical aspects are not just an afterthought but integral components of the model development and deployment process. This article delves into the world of SageMaker Clarify, offering a comprehensive guide to its capabilities and practical applications. We commence our journey with a high-level understanding of what SageMaker Clarify is and its importance in the day-to-day tasks of machine learning modeling. Our exploration is anchored in a hands-on example, utilizing a specially crafted dataset that simulates loan [...]

Amazon AI Fairness and Explainability with Amazon SageMaker Clarify2023-12-02T01:24:03+00:00

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